[SciPy-User] leastsq returns bizarre, not fitted, output for float values
Thu Jun 10 10:35:59 CDT 2010
On Thu, Jun 10, 2010 at 11:15 AM, Charles R Harris
> On Thu, Jun 10, 2010 at 8:10 AM, Charles R Harris
> <email@example.com> wrote:
>> On Thu, Jun 10, 2010 at 8:02 AM, Matthieu Rigal <firstname.lastname@example.org> wrote:
>>> OK, I've found the bug...
>>> Somehow the leastsq function is not working if both data sets are float
>>> By just adding following line the problem is solved :
>>> aX = numpy.asarray(aX, dtype=numpy.float64)
>>> Is it a known bug ? Should I add it to the bug tracker ?
>>> Best regards,
>> I think you should open a ticket and include a simple example.
> I also note that the documentation of leastsq is totally screwed up and the
> covariance returned is not the covariance, nor is it the currently
> documented Jacobian.
cov_x is the raw covariance, what's wrong with the explanation
I never figured out how to get the Jacobian directly, and am not sure
about the details of the jacobian calculation
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